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acge_text_embedding

Sentence Similarity
sentence-transformers
PyTorch
Safetensors
bert
mteb
feature-extraction
Eval Results
text-embeddings-inference
Inference Endpoints
Model card Files Community
16
acge_text_embedding
File size: 1,418 Bytes 
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{
  "dataset_revision": null,
  "mteb_dataset_name": "Cmnli",
  "mteb_version": "1.1.1",
  "validation": {
    "cos_sim": {
      "accuracy": 0.834155141310884,
      "accuracy_threshold": 0.655905544757843,
      "ap": 0.9049057754163061,
      "f1": 0.8427460263780859,
      "f1_threshold": 0.645372748374939,
      "precision": 0.8136700043535046,
      "recall": 0.8739770867430442
    },
    "dot": {
      "accuracy": 0.8342754058929646,
      "accuracy_threshold": 0.6557313203811646,
      "ap": 0.9050212054081632,
      "f1": 0.8431416424255985,
      "f1_threshold": 0.6397272348403931,
      "precision": 0.8084102124007724,
      "recall": 0.8809913490764555
    },
    "euclidean": {
      "accuracy": 0.8345159350571256,
      "accuracy_threshold": 0.8281130194664001,
      "ap": 0.9048986952292054,
      "f1": 0.8430311231393776,
      "f1_threshold": 0.8416151404380798,
      "precision": 0.8142016989762579,
      "recall": 0.8739770867430442
    },
    "evaluation_time": 6.59,
    "manhattan": {
      "accuracy": 0.8353577871316897,
      "accuracy_threshold": 28.042278289794922,
      "ap": 0.9048090090749703,
      "f1": 0.8442074208555542,
      "f1_threshold": 28.250762939453125,
      "precision": 0.8201058201058201,
      "recall": 0.8697685293429974
    },
    "max": {
      "accuracy": 0.8353577871316897,
      "ap": 0.9050212054081632,
      "f1": 0.8442074208555542
    }
  }
}